Development of an online computational platform for the analysis of protein synthesis and detection of novel translated regions

Ribosome profiling is a technique that allows us to capture and sequence mRNA fragments protected by ribosome complexes. Mapping these ribosome protected fragments or RPFs, back to a genome or transcriptome provides information on the precise location of elongating ribosomes. This data can then be used to detect novel translated regions, translational pausing and differentially translated genes. Chapter 2 describes the development of Trips-Viz, an interactive online platform for the exploration and visualisation of RPFs mapped to the transcriptomes of various different organisms. This allows users to rapidly aggregate and visualise ribosome profiling data at a single transcript level allowing for visual detection of translated open reading frames. Trips-Viz also allows users to rapidly assess the quality of data through various meta-information plots as well as detect and visualise transcripts that are differentially expressed/translated between two conditions. These analyses can be carried out through a GUI, meaning users do not need any prior coding or command line experience to be able to use them. Chapter 3 describes the major updates made to Trips-Viz since its original publication. This includes the addition of mass spectrometry data. Several thousand human mass spectrometry datasets have been processed and detected peptides mapped to the human transcriptome in the same manner as ribosome profiling data. This allows users to corroborate the evidence from the ribosome profiling data and provides information on whether a translated ORF is capable of producing a stable protein product. The differential expression/translation detection has also been improved with the inclusion of the Deseq2 and Anota2seq software. A method for the automatic detection of translated ORFs was also included which allows users to find translated uORFs, nested ORFs, downstream ORFs in a relatively timely manner. Other improvements include the addition of help videos to guide users through the navigation and interacting with the users interface of Trips-Viz. Finally, incorporating the relevant scripts into RiboGalaxy made it easier for users to upload their own data and transcriptomes to Trips-Viz without any requirement for command line expertise

The GWIPS-viz browser

GWIPS-viz is a publicly available browser that provides Genome Wide Information on Protein Synthesis through the visualization of ribosome profiling data. Ribosome profiling (Ribo-seq) is a high-throughput technique which isolates fragments of messenger RNA that are protected by the ribosome. The alignment of the ribosome-protected fragments or footprint sequences to the corresponding reference genome and their visualization using GWIPS-viz allows for unique insights into the genome loci that are expressed as potentially translated RNA. The GWIPS-viz browser hosts both Ribo-seq data and corresponding mRNA-seq data from publicly available studies across a number of genomes, avoiding the need for computational processing on the user side. Since its initial publication in 2014, over 1885 tracks have been produced across 24 genomes. This unit describes the navigation of the GWIPS-viz genome browser, the uploading of custom tracks, and the downloading of the Ribo-seq/mRNA-seq alignment data

Computational methods for ribosome profiling data analysis

Since the introduction of the ribosome profiling technique in 2009 its popularity has greatly increased. It is widely used for the comprehensive assessment of gene expression and for studying the mechanisms of regulation at the translational level. As the number of ribosome profiling datasets being produced continues to grow, so too does the need for reliable software that can provide answers to the biological questions it can address. This review describes the computational methods and tools that have been developed to analyze ribosome profiling data at the different stages of the process. It starts with initial routine processing of raw data and follows with more specific tasks such as the identification of translated open reading frames, differential gene expression analysis, or evaluation of local or global codon decoding rates. The review pinpoints challenges associated with each step and explains the ways in which they are currently addressed. In addition it provides a comprehensive, albeit incomplete, list of publicly available software applicable to each step, which may be a beneficial starting point to those unexposed to ribosome profiling analysis. The outline of current challenges in ribosome profiling data analysis may inspire computational biologists to search for novel, potentially superior, solutions that will improve and expand the bioinformatician's toolbox for ribosome profiling data analysis

GWIPS-viz: 2018 update

The GWIPS-viz browser (http://gwips.ucc.ie/) is an on-line genome browser which is tailored for exploring ribosome profiling (Ribo-seq) data. Since its publication in 2014, GWIPS-viz provides Ribo-seq data for an additional 14 genomes bringing the current total to 23. The integration of new Ribo-seq data has been automated thereby increasing the number of available tracks to 1792, a 10-fold increase in the last three years. The increase is particularly substantial for data derived from human sources. Following user requests, we added the functionality to download these tracks in bigWig format. We also incorporated new types of data (e.g. TCP-seq) as well as auxiliary tracks from other sources that help with the interpretation of Ribo-seq data. Improvements in the visualization of the data have been carried out particularly for bacterial genomes where the Ribo-seq data are now shown in a strand specific manner. For higher eukaryotic datasets, we provide characteristics of individual datasets using the RUST program which includes the triplet periodicity, sequencing biases and relative inferred A-site dwell times. This information can be used for assessing the quality of Ribo-seq datasets. To improve the power of the signal, we aggregate Ribo-seq data from several studies into Global aggregate tracks for each genome

TASEP modelling provides a parsimonious explanation for the ability of a single uORF to derepress translation during the integrated stress response

Translation initiation is the rate-limiting step of protein synthesis that is downregulated during the Integrated Stress Response (ISR). Previously, we demonstrated that most human mRNAs that are resistant to this inhibition possess translated upstream open reading frames (uORFs), and that in some cases a single uORF is sufficient for the resistance. Here we developed a computational model of Initiation Complexes Interference with Elongating Ribosomes (ICIER) to gain insight into the mechanism. We explored the relationship between the flux of scanning ribosomes upstream and downstream of a single uORF depending on uORF features. Paradoxically, our analysis predicts that reducing ribosome flux upstream of certain uORFs increases initiation downstream. The model supports the derepression of downstream translation as a general mechanism of uORF-mediated stress resistance. It predicts that stress resistance can be achieved with long slowly decoded uORFs that do not favor translation reinitiation and that start with initiators of low leakiness

Trips-Viz: an environment for the analysis of public and user-generated ribosome profiling data.

Trips-Viz (https://trips.ucc.ie/) is an interactive platform for the analysis and visualization of ribosome profiling (Ribo-Seq) and shotgun RNA sequencing (RNA-seq) data. This includes publicly available and user generated data, hence Trips-Viz can be classified as a database and as a server. As a database it provides access to many processed Ribo-Seq and RNA-seq data aligned to reference transcriptomes which has been expanded considerably since its inception. Here, we focus on the server functionality of Trips-viz which also has been greatly improved. Trips-viz now enables visualisation of proteomics data from a large number of processed mass spectrometry datasets. It can be used to support translation inferred from Ribo-Seq data. Users are now able to upload a custom reference transcriptome as well as data types other than Ribo-Seq/RNA-Seq. Incorporating custom data has been streamlined with RiboGalaxy (https://ribogalaxy.ucc.ie/) integration. The other new functionality is the rapid detection of translated open reading frames (ORFs) through a simple easy to use interface. The analysis of differential expression has been also improved via integration of DESeq2 and Anota2seq in addition to a number of other improvements of existing Trips-viz features

Trips-Viz: A transcriptome browser for exploring Ribo-Seq data

Ribosome profiling (Ribo-Seq) is a technique that allows for the isolation and sequencing of mRNA fragments protected from nuclease digestion by actively translating ribosomes. Mapping these ribosome footprints to a genome or transcriptome generates quantitative information on translated regions. To provide access to publicly available ribosome profiling data in the context of transcriptomes we developed Trips-Viz (transcriptome-wide information on protein synthesis-visualized). Trips-Viz provides a large range of graphical tools for exploring global properties of translatomes and of individual transcripts. It enables analysis of aligned footprints to evaluate datasets quality, differential gene expression detection, visual identification of upstream ORFs and alternative proteoforms. Trips-Viz is available at https://trips.ucc.ie

AMD1 mRNA employs ribosome stalling as a mechanism for molecular memory formation.

In addition to acting as template for protein synthesis, messenger RNA (mRNA) often contains sensory sequence elements that regulate this process1,2. Here we report a new mechanism that limits the number of complete protein molecules that can be synthesized from a single mRNA molecule of the human AMD1 gene encoding adenosylmethionine decarboxylase 1 (AdoMetDC). A small proportion of ribosomes translating AMD1 mRNA stochastically read through the stop codon of the main coding region. These readthrough ribosomes then stall close to the next in-frame stop codon, eventually forming a ribosome queue, the length of which is proportional to the number of AdoMetDC molecules that were synthesized from the same AMD1 mRNA. Once the entire spacer region between the two stop codons is filled with queueing ribosomes, the queue impinges upon the main AMD1 coding region halting its translation. Phylogenetic analysis suggests that this mechanism is highly conserved in vertebrates and existed in their common ancestor. We propose that this mechanism is used to count and limit the number of protein molecules that can be synthesized from a single mRNA template. It could serve to safeguard from dysregulated translation that may occur owing to errors in transcription or mRNA damage

Cellular gene expression during Hepatitis C virus replication as revealed by Ribosome Profiling

Background: Hepatitis C virus (HCV) infects human liver hepatocytes, often leading to liver cirrhosis and hepatocellular carcinoma (HCC). It is believed that chronic infection alters host gene expression and favors HCC development. In particular, HCV replication in Endoplasmic Reticulum (ER) derived membranes induces chronic ER stress. How HCV replication affects host mRNA translation and transcription at a genome wide level is not yet known. Methods: We used Riboseq (Ribosome Profiling) to analyze transcriptome and translatome changes in the Huh-7.5 hepatocarcinoma cell line replicating HCV for 6 days. Results: Established viral replication does not cause global changes in host gene expression—only around 30 genes are significantly differentially expressed. Upregulated genes are related to ER stress and HCV replication, and several regulated genes are known to be involved in HCC development. Some mRNAs (PPP1R15A/GADD34, DDIT3/CHOP, and TRIB3) may be subject to upstream open reading frame (uORF) mediated translation control. Transcriptional downregulation mainly affects mitochondrial respiratory chain complex core subunit genes. Conclusion: After establishing HCV replication, the lack of global changes in cellular gene expression indicates an adaptation to chronic infection, while the downregulation of mitochondrial respiratory chain genes indicates how a virus may further contribute to cancer cell-like metabolic reprogramming (“Warburg effect”) even in the hepatocellular carcinoma cells used here

skiniry/Trips-Viz

Trips-viz is a transcriptome browser designed to visualize Ribosome profiling and RNA-seq data at the level of a single gene/transcript isoform as opposed to at the genome level. Trips-viz also provides you the ability to vizualize data from a gene under different conditions, get meta-information at an individual dataset level such as read length distribution or triplet periodicity, and provides the ability to find differentially expressed or translated genes